{"title":"An overview of wind power probabilistic forecasts","authors":"Yuan-Kang Wu, Po-En Su, Jing-Shan Hong","doi":"10.1109/APPEEC.2016.7779540","DOIUrl":null,"url":null,"abstract":"Over the past one to two decades, probabilistic forecasts have become more popular. Probabilistic forecasts take uncertainty into account and predict a probability distribution function (pdf). This study provides an overview of state-of-the-art technologies on wind-power probabilistic forecasts, and describes the fundamental concepts on those forecasting methods. Additionally, this study also summarizes various methods to evaluate the performance of a probabilistic forecast model. Finally, this study presents a case study using the ensemble prediction model, in which the wind-speed data were provided by the numerical weather prediction system (NWP) of the Central Weather Bureau (CWB) of Taiwan.","PeriodicalId":117485,"journal":{"name":"2016 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APPEEC.2016.7779540","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 16
Abstract
Over the past one to two decades, probabilistic forecasts have become more popular. Probabilistic forecasts take uncertainty into account and predict a probability distribution function (pdf). This study provides an overview of state-of-the-art technologies on wind-power probabilistic forecasts, and describes the fundamental concepts on those forecasting methods. Additionally, this study also summarizes various methods to evaluate the performance of a probabilistic forecast model. Finally, this study presents a case study using the ensemble prediction model, in which the wind-speed data were provided by the numerical weather prediction system (NWP) of the Central Weather Bureau (CWB) of Taiwan.